test

app.py

@@ -10,6 +10,7 @@ and playable instead of buried in a bullet point.
 
 import gradio as gr
 import numpy as np
+import pandas as pd
 import spaces
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
@@ -87,6 +88,39 @@ EXAMPLE_QUERIES = [
     "What certifications do you have?",
 ]
 
+# ---------------------------------------------------------------------------
+# Leaderboard-style tables — sortable, scannable, MTEB-inspired.
+# ---------------------------------------------------------------------------
+SKILLS_DF = pd.DataFrame([
+    {"Category": "AI/ML & GenAI", "Skills": "LLMs, Generative AI, Agentic AI, Prompt Engineering, Semantic Search, Classification, Regression, Decision Trees, SMOTE, OCR/NLP"},
+    {"Category": "Programming", "Skills": "Python, JavaScript, Node.js"},
+    {"Category": "Cloud & MLOps", "Skills": "Microsoft Azure, Azure SQL, Azure Blob, Serverless, Virtual Machines, CI/CD"},
+    {"Category": "Tools & Practices", "Skills": "Git, GitHub, Jira, Azure DevOps, Snyk, Wiz, Agile"},
+])
+
+IMPACT_DF = pd.DataFrame([
+    {"Metric": "Hackathon placement", "Company": "Flexday AI (INFERA)", "Result": "🏆 1st"},
+    {"Metric": "Semantic search retrieval improvement", "Company": "Flexday AI", "Result": "+50%"},
+    {"Metric": "Infrastructure cost reduction", "Company": "Leokraft", "Result": "-20%"},
+    {"Metric": "ML model accuracy improvement", "Company": "Leokraft", "Result": "+8%"},
+    {"Metric": "Feature-engineering accuracy gain", "Company": "Leokraft", "Result": "+5%"},
+    {"Metric": "Process cycle-time reduction", "Company": "Flexday AI", "Result": "-5%"},
+    {"Metric": "Students taught (full-stack web dev)", "Company": "CodingZen", "Result": "100+"},
+])
+
+CERTS_DF = pd.DataFrame([
+    {"Certification": "Building with the Claude API", "Focus": "LLM application development"},
+    {"Certification": "Generative AI (Professional Certificate)", "Focus": "Generative AI fundamentals"},
+    {"Certification": "AI Fluency: Framework & Foundations", "Focus": "Applied AI literacy"},
+    {"Certification": "Machine Learning for Leaders", "Focus": "ML strategy"},
+    {"Certification": "Analyze Box Office Data with Seaborn and Python", "Focus": "Data analysis & visualization"},
+])
+
+EDUCATION_DF = pd.DataFrame([
+    {"Degree": "M.Tech, Information Technology", "Institution": "Tezpur University", "Years": "2019–2021", "Highlight": "Distinction, 8.69 CGPA, full AICTE scholarship"},
+    {"Degree": "B.Tech, Computer Science & Engineering", "Institution": "KIET Group of Institutions", "Years": "2012–2016", "Highlight": "First Division"},
+])
+
 # ---------------------------------------------------------------------------
 # Styling — dark "console" theme matching the static-site edition
 # ---------------------------------------------------------------------------
@@ -154,6 +188,33 @@ CUSTOM_CSS = """
 .gradio-container button:hover {
     transform: translateY(-2px);
 }
+.tabs > .tab-nav {
+    border-bottom: 1px solid #2a3040 !important;
+    gap: 4px !important;
+}
+.tabs > .tab-nav button {
+    font-family: monospace !important;
+    font-size: 13px !important;
+    color: #9aa3b5 !important;
+    border: none !important;
+    background: transparent !important;
+    padding: 10px 16px !important;
+}
+.tabs > .tab-nav button.selected {
+    color: var(--amber) !important;
+    border-bottom: 2px solid var(--amber) !important;
+    font-weight: 600 !important;
+}
+table {
+    font-size: 13.5px !important;
+}
+thead th {
+    font-family: monospace !important;
+    text-transform: uppercase !important;
+    font-size: 11px !important;
+    letter-spacing: 0.06em !important;
+    color: var(--amber) !important;
+}
 """
 
 with gr.Blocks(title="Angkit Sarma — Living CV") as demo:
@@ -192,86 +253,79 @@ with gr.Blocks(title="Angkit Sarma — Living CV") as demo:
     ask_btn.click(fn=ask_the_cv, inputs=[query_box, chatbot], outputs=[chatbot, query_box])
     query_box.submit(fn=ask_the_cv, inputs=[query_box, chatbot], outputs=[chatbot, query_box])
 
-    gr.HTML('<p class="section-label">// summary</p>')
-    gr.Markdown(
-        "Results-driven AI/ML Engineer with 4+ years designing, training, and deploying machine "
-        "learning and generative AI systems that solve real business problems. Proven track record "
-        "building agentic AI and LLM-powered applications, optimizing semantic search and NLP "
-        "pipelines, and automating end-to-end ML workflows from data processing to production "
-        "deployment. Combines strong ML engineering fundamentals with cloud deployment, MLOps, and "
-        "application security expertise to ship secure, scalable, high-impact AI solutions."
-    )
+    with gr.Tabs():
+        with gr.Tab("Overview"):
+            gr.Markdown(
+                "Results-driven AI/ML Engineer with 4+ years designing, training, and deploying machine "
+                "learning and generative AI systems that solve real business problems. Proven track record "
+                "building agentic AI and LLM-powered applications, optimizing semantic search and NLP "
+                "pipelines, and automating end-to-end ML workflows from data processing to production "
+                "deployment. Combines strong ML engineering fundamentals with cloud deployment, MLOps, and "
+                "application security expertise to ship secure, scalable, high-impact AI solutions."
+            )
+            gr.HTML('<p class="section-label" style="margin-top:22px;">// impact metrics</p>')
+            gr.Dataframe(
+                value=IMPACT_DF, interactive=False, wrap=True,
+                column_widths=["55%", "25%", "20%"],
+            )
 
-    gr.HTML('<p class="section-label">// experience</p>')
-    with gr.Accordion("Software Developer (AI/ML Focus) — Flexday AI, Hyderabad · Nov 2022 – Present", open=True):
-        gr.Markdown(
-            "- Built and pitched **INFERA**, an AI-powered agentic solution that maps sales projects "
-            "to real-world opportunities — 1st place at the Flexday AI Hackathon\n"
-            "- Optimized a semantic search system using LLM/embedding-based techniques, improving "
-            "retrieval performance by **50%**\n"
-            "- Designed automated, AI-assisted workflows across departments, cutting process cycle "
-            "time by 5% and freeing 10+ hours/month\n"
-            "- Implemented OCR-based data extraction pipelines across diverse image collections\n"
-            "- Identified and remediated critical security vulnerabilities, mitigating million-dollar "
-            "risk exposure\n"
-            "- Streamlined CI/CD build pipelines using Git, GitHub, Jira, and Azure DevOps"
-        )
-    with gr.Accordion("Machine Learning Engineer — Leokraft Technologies, Bangalore · Dec 2021 – Dec 2022", open=False):
-        gr.Markdown(
-            "- Designed, trained, and deployed end-to-end ML models into production, improving "
-            "accuracy by **8%** while cutting infrastructure costs by **20%**\n"
-            "- Engineered a key target-variable feature that improved model accuracy by 5%\n"
-            "- Built an end-to-end application for managing model scores and usage statistics"
-        )
-    with gr.Accordion("Senior Faculty — CodingZen, Delhi · Jul 2018 – Jul 2019", open=False):
-        gr.Markdown(
-            "- Taught 100+ students full-stack web development with Node.js\n"
-            "- Supervised and mentored a team of teaching staff"
-        )
+        with gr.Tab("Experience"):
+            with gr.Accordion("Software Developer (AI/ML Focus) — Flexday AI, Hyderabad · Nov 2022 – Present", open=True):
+                gr.Markdown(
+                    "- Built and pitched **INFERA**, an AI-powered agentic solution that maps sales projects "
+                    "to real-world opportunities — 1st place at the Flexday AI Hackathon\n"
+                    "- Optimized a semantic search system using LLM/embedding-based techniques, improving "
+                    "retrieval performance by **50%**\n"
+                    "- Designed automated, AI-assisted workflows across departments, cutting process cycle "
+                    "time by 5% and freeing 10+ hours/month\n"
+                    "- Implemented OCR-based data extraction pipelines across diverse image collections\n"
+                    "- Identified and remediated critical security vulnerabilities, mitigating million-dollar "
+                    "risk exposure\n"
+                    "- Streamlined CI/CD build pipelines using Git, GitHub, Jira, and Azure DevOps"
+                )
+            with gr.Accordion("Machine Learning Engineer — Leokraft Technologies, Bangalore · Dec 2021 – Dec 2022", open=False):
+                gr.Markdown(
+                    "- Designed, trained, and deployed end-to-end ML models into production, improving "
+                    "accuracy by **8%** while cutting infrastructure costs by **20%**\n"
+                    "- Engineered a key target-variable feature that improved model accuracy by 5%\n"
+                    "- Built an end-to-end application for managing model scores and usage statistics"
+                )
+            with gr.Accordion("Senior Faculty — CodingZen, Delhi · Jul 2018 – Jul 2019", open=False):
+                gr.Markdown(
+                    "- Taught 100+ students full-stack web development with Node.js\n"
+                    "- Supervised and mentored a team of teaching staff"
+                )
 
-    gr.HTML('<p class="section-label">// projects</p>')
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("**INFERA** — Agentic AI Sales-Opportunity Mapper\n\n*LLMs · AI Agents · Python*\n\nAn AI agent that analyzes sales pipeline data and autonomously maps projects to real-world business opportunities.\n\n🏆 1st Place — Flexday AI Hackathon")
-        with gr.Column():
-            gr.Markdown("**Analytica** — End-to-End ML Analytics Platform\n\n*React · Python · Azure · SQL*\n\nFull-stack analytics tool surfacing ML model performance metrics and usage statistics.")
-        with gr.Column():
-            gr.Markdown("**Predictive Allocation** — ML Deployment Pipeline\n\n*Python · Azure SQL · Azure Blob · DevOps*\n\nRe-engineered end-to-end training/deployment pipeline; hardened security with Snyk and Wiz.")
-    gr.HTML(
-        '<p style="font-family:monospace; font-size:13px; margin-top:6px;">'
-        '<a href="https://github.com/angkit-hash" target="_blank" style="color:#4fd1c5; text-decoration:none; border-bottom:1px solid #4fd1c5;">'
-        '→ View source &amp; more projects on GitHub</a></p>'
-    )
+        with gr.Tab("Projects"):
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown("**INFERA** — Agentic AI Sales-Opportunity Mapper\n\n*LLMs · AI Agents · Python*\n\nAn AI agent that analyzes sales pipeline data and autonomously maps projects to real-world business opportunities.\n\n🏆 1st Place — Flexday AI Hackathon")
+                with gr.Column():
+                    gr.Markdown("**Analytica** — End-to-End ML Analytics Platform\n\n*React · Python · Azure · SQL*\n\nFull-stack analytics tool surfacing ML model performance metrics and usage statistics.")
+                with gr.Column():
+                    gr.Markdown("**Predictive Allocation** — ML Deployment Pipeline\n\n*Python · Azure SQL · Azure Blob · DevOps*\n\nRe-engineered end-to-end training/deployment pipeline; hardened security with Snyk and Wiz.")
+            gr.HTML(
+                '<p style="font-family:monospace; font-size:13px; margin-top:10px;">'
+                '<a href="https://github.com/angkit-hash" target="_blank" style="color:#4fd1c5; text-decoration:none; border-bottom:1px solid #4fd1c5;">'
+                '→ View source &amp; more projects on GitHub</a></p>'
+            )
 
-    gr.HTML('<p class="section-label">// skills</p>')
-    gr.Markdown(
-        "**AI/ML & GenAI:** LLMs · Generative AI · Agentic AI · Prompt Engineering · Semantic Search · "
-        "Classification · Regression · Decision Trees · SMOTE · OCR/NLP\n\n"
-        "**Programming:** Python · JavaScript · Node.js\n\n"
-        "**Cloud & MLOps:** Microsoft Azure · Azure SQL · Azure Blob · Serverless · Virtual Machines · CI/CD\n\n"
-        "**Tools & Practices:** Git · GitHub · Jira · Azure DevOps · Snyk · Wiz · Agile"
-    )
+        with gr.Tab("Skills"):
+            gr.Dataframe(
+                value=SKILLS_DF, interactive=False, wrap=True,
+                column_widths=["25%", "75%"],
+            )
 
-    gr.HTML('<p class="section-label">// certifications & education</p>')
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown(
-                "**Certifications & Honors**\n\n"
-                "- Building with the Claude API\n"
-                "- Generative AI (Professional Certificate)\n"
-                "- AI Fluency: Framework & Foundations\n"
-                "- Machine Learning for Leaders\n"
-                "- Analyze Box Office Data with Seaborn and Python\n"
-                "- 1st Place — Flexday AI Hackathon (INFERA)"
+        with gr.Tab("Certifications & Education"):
+            gr.HTML('<p class="section-label">Certifications</p>')
+            gr.Dataframe(
+                value=CERTS_DF, interactive=False, wrap=True,
+                column_widths=["55%", "45%"],
             )
-        with gr.Column():
-            gr.Markdown(
-                "**Education**\n\n"
-                "**M.Tech, Information Technology** — Tezpur University · 2019–2021\n"
-                "- Graduated with Distinction — 8.69 CGPA\n"
-                "- Full-time AICTE scholarship recipient\n\n"
-                "**B.Tech, Computer Science & Engineering** — KIET · 2012–2016\n"
-                "- Secured First Division"
+            gr.HTML('<p class="section-label" style="margin-top:22px;">Education</p>')
+            gr.Dataframe(
+                value=EDUCATION_DF, interactive=False, wrap=True,
+                column_widths=["30%", "28%", "14%", "28%"],
             )
 
 if __name__ == "__main__":

requirements.txt

@@ -2,3 +2,4 @@ gradio==6.20.0
 spaces
 scikit-learn>=1.3
 numpy>=1.24
+pandas>=2.0